where p is spatial position, \(f_{1}\)  represents a convolution operation with filter size \(3\times 3\) , \(\delta \)  refers to activation function ReLU [1]} and \(\sigma \)  is a sigmoid activation function used to generate spatial weight \(t_{h, w} \in (0, 1)\)  at position (h, w).
T is finally applied to the feature map F. The feature values at different positions in F are multiplied by different weights in T to generate the output O of the spatial attention block as:
\(O_{hw} \ = \ f_{hw}\cdot t_{hw}\) 
